Abstract
The number of visualizations being required for a complete view on data non-linearly grows with the number of data dimensions. Thus, relevant visualizations need to be filtered to guide the user during the visual search. A popular filter approach is the usage of quality metrics, which map a visual pattern to a real number. This way, visualizations that contain interesting patterns are automatically detected. Quality metrics are a useful tool in visual analysis, if they resemble the human perception. In this work we present a broad study to examine the relation between filtering relevant visualizations based on human perception versus quality metrics. For this, seven widely-used quality metrics were tested on five high-dimensional datasets, covering scatterplots, parallel coordinates, and radial visualizations. In total, 102 participants were available. The results of our studies show that quality metrics often work similar to the human perception. Interestingly, a subset of so-called Scagnostic measures does the best job.
About the authors
Dirk J. Lehmann is a Postdoctoral Research Fellow at the Computer Science Department at the University of Magdeburg, Germany. In 2008, he received the M.Sc. in Computational Visualistics and in 2012 a Ph.D. in Computer Science from the University of Magdeburg. His research interests focus on flow visualization, information visualization, and visual analytics.
Otto-von-Guericke-Universität, Fakultät für Informatik, Universitätsplatz 2, 39106 Magdeburg
Sebastian Hundt successfully studied Comptational Visualistics and received a M.Sc. from the University of Magdeburg in 2012. His research interests focus on information visualization, computer graphics, and visual analytics. Recently, he left the university for industry.
Otto-von-Guericke-Universität, Fakultät für Informatik, Universitätsplatz 2, 39106 Magdeburg
Holger Theisel is professor for Visual Computing at the Computer Science Department at the University of Magdeburg, Germany. In 1994, he received the diploma in Computer Science, in 1996 a Ph.D. in Computer Science, and a habilitation (venia legendi) in 2001 from the University of Rostock. His research interests focus on flow and volume visualization as well as on CAGD, geometry processing and information visualization.
Otto-von-Guericke-Universität, Fakultät für Informatik, Universitätsplatz 2, 39106 Magdeburg
©2015 Walter de Gruyter Berlin/Boston
